Title: Replication Package for “Secessionism and Wartime Sexual Violence”

Journal: Journal of Conflict Resolution

Dataverse: https://dataverse.harvard.edu/ | Replication Package DOI: https://doi.org/10.7910/DVN/KK4SCA

Author: Changwook Ju (cwju@stanford.edu) | Institution: Stanford University (Center for International Security and Cooperation)

Date: February 3, 2025

Computing Environment: x64-based processor (64-bit) under Windows 11 Home

License and Rights: Per journal or dataverse policy

Data Source: Sources for imported data are documented in the `data.dta` file and Table 1 of the article.

Variable Labels for Replication Data: Labels for all variables are included in the `data.dta` file.

Software: R (Version 4.4.2)

Software Packages and Libraries: Requisite R packages are specified in each programming file.

Replication: To replicate all analyses and figures, (1) download the replication data files to a folder entitled “~/data”, 
				     		    (2) create a second folder entitled “~/results” in the same directory,
				       		    (3) create a third folder entitled “~/figures” in the same directory,
				       		    (4) create four sub-folders within “~/figures” named “~/figures/summary plots”,
													 “~/figures/tree”, 
													 “~/figures/coefficient plots”, and
													 “~/figures/predicted probability plots”, and
				       		    (5) run all code files in numerical order.

Note: R programming files contain organized sections. Use the following shortcuts to better navigate R(Studio).

      Alt + L: Collapse active section
      Alt + O: Collapse all sections
      Shift + Alt + L: Expand active sections
      Shift + Alt + O: Expand all sections

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%% Replication Data (relative path “~/data”) %%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[1] data.dta
- Data for main analysis, robustness checks 1–5, and longitudinal analysis

[2] data_cs.dta
- Cross-sectional data for robustness check 6

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%% Code for Analysis %%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[1] 1. analysis.Rmd
- Conducts (zero-inflated) ordered probit analysis
- Uses `Statamarkdown` to execute both Stata and R commands in RStudio

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%% Results (relative path “~/results”) %%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[1] main_rebel.dta
[2] main_rebel_pp.dta
[3] main_rebel_inflated0_pp.dta
[4] main_rebel_true0_pp.dta
[5] main_state.dta
[6] main_state_pp.dta
[7] main_state_inflated0_pp.dta
[8] main_state_true0_pp.dta
[9] main_rebel_op.dta
[10] main_state_op.dta
[11] rc1_rebel.dta
[12] rc1_state.dta
[13] rc2_rebel.dta
[14] rc2_state.dta
[15] rc3_rebel.dta
[16] rc3_state.dta
[17] rc4_rebel.dta
[18] rc4_state.dta
[19] rc5_rebel.dta
[20] rc5_state.dta
[21] rc6_rebel.dta
[22] rc6_state.dta
[23] longitudinal_rebel.dta
[24] longitudinal_rebel_pp.dta
[25] longitudinal_rebel_inflated0_pp.dta
[26] longitudinal_rebel_true0_pp.dta
[27] longitudinal_state.dta
[28] longitudinal_state_pp.dta
[29] longitudinal_state_inflated0_pp.dta
[30] longitudinal_state_true0_pp.dta

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%% Code for Figures %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[1] 2. summary_plots.R
- Creates Figures 1, 2, A.1, and C.7

[2] 3. tree.R
- Creates Figure 3

[3] 4. coefficient_plots.R
- Creates Figures 4, 6, B.1, C.1–6, and D.1

[4] 5. predicted_probability_plots.R
- Creates Figures 5, 7, B.2, and D.2
